The Australian Guidelines for Water Recycling – Managed Aquifer Recharge provide a ready-to -use and user-friendly compendium of knowledge. Practical instructions and checklists provide a step wise approach with a strong focus on implementation. The proposed models for water flow and substance transport allow a first tier estimation of present concentrations in ambient groundwater and the impacted zone in the aquifer. The use of stochastic models is not mandatory within the guidelines. A criticism which can be identified related to the use of models simply based on point estimates, is that especially in early stage risk assessments, where uncertainties are usually high, these models tend to pretend a level of certainty which often does not represent reality. Risks associated to inorganic chemicals are required to be treated with more detail. Rigorous quantification of biodegradation kinetics (e.g. first-order rate constants) and adsorption parameters (e.g. linear distribution coefficients) for EOCs during subsurface passage determined on field scale are still scarce. It is clear that first-order rate constants and linear distribution coefficients provide only a simplified description of the removal mechanisms during subsurface passage, because they neglect spatial and temporal dynamics of physical and chemical conditions. Nevertheless, this approach often provides a good approximation and allows also for site independent comparison of removal processes. Regarding the demonstration site in Berlin-Tegel the analysis showed that if the model of the Australian Guidelines is applied to the MAR system the travel time of 50d during subsurface passage cannot be guaranteed. In Germany, a residence time of 50d is usually considered to sufficiently reduce the risk of microbial hazards. Although risk calculations did not reveal immediate concern, it is recommended to develop and apply suitable verification monitoring techniques to quantify travel times and reduce present uncertainties. Moreover, this risk assessment and the study about the influence of the groundwater replenishment site on ambient groundwater (Sprenger and Grützmacher, 2015) clearly showed the need for protective measures against the input of undesired substances from shallow ambient groundwater.

Micropollutant concentrations found in stormwater runoff were extrapolated to annual loads at the scale of the city of Berlin (impervious connected area of ~170 km2). Extrapolation was done by city structure, i.e., it was assumed that concentration patterns found in one of five specific city structure types is representative for every area of this structure type. Preliminary results show that micropollutants of several substance types can enter Berlin surface waters at loads in the order of kg/yr via stormwater runoff: plasticizers (e.g., sum of Di-iso-decylphthalate and Di-iso-nonylphthalate at 770 kg/yr), flame retardants (e.g., tris(2-butoxyethyl) phosphate (TBEP) at 89 kg/yr), biocides from different sources (e.g., Glyphosate at 17 kg/yr and Mecoprop at 30 kg/yr), vulcanizing accelerator benzothiazole (as sum of benzothiazole and metabolites methylthiobenzothiazole and hydroxybenzothiazole at 65 kg/yr) and combustion byproduct polycyclic aromatic hydrocarbons PAH 16 (sum of 16 EPA PAH at 107 kg/yr). These loads are in a similar order of magnitude as micropollutants that enter Berlin surface waters via (treated) sewage, such as pharmaceutical residues carbamazepine and ibuprofen with estimated annual loads of 436 kg/yr and 35 kg/yr, respectively.

In recent years, the effect of urbanization on the quality of stormwater runoff gained increased attention including investigations on micropollutants. Especially in cities dominated by separated sewer systems, stormwater runoff containing micropollutants from anthropogenic origin is discharged mostly untreated into surface waters and therefore a potential source of high loads of pollutants. In a one year monitoring campaign stormwater runoff from five different catchments in Berlin is analyzed for major groups of micropollutants such as phthalates, organophosphates, organotin-compounds, biocides/pesticides, PAH’s, alkylphenols, polybrominated diphenylether, polychlorinated biphenyls and heavy metals. Sampling sites are equipped with automatic samplers, flow and water level meters in order to prepare flow proportional composite samples (recommended sampling strategy according to DIN ISO 5667-10). First results show that all groups of micropollutants were found in at least one catchment type in concentrations > 2 µg/L. Concentrations of the different micropollutant groups vary depending on the catchment types. So far, no organotin-compounds, polybrominated diphenylether or polychlorinated biphenyls were determined.

Untreated stormwater runoff can be an important source of pollutants affecting urban surface waters. For example, in Berlin each year 78% or 54 million m³ of stormwater are discharged mostly untreated into receiving surface waters. Beside “classic” stormwater pollutants (e.g. suspended solids, COD, phosphorous or heavy metals), trace organic substances such as biocides, plasticizers, flame retardants and traffic related micropollutants (e.g. vulcanizing accelerators originating from tire wear or combustion by-products such as PAHs) started to come into focus in recent years (Zgheib et al. 2012, Gasperi et al. 2014). To evaluate for the first time city-wide annual loads of these trace organic substances entering urban surface waters through stormwater discharge, an event-based, one-year monitoring program was set up in the city of Berlin.

A study is conducted to determine the relevance of micropollutants in urban stormwater runoff. To evaluate for the first time city-wide annual loads of stormwater-based micropollutants entering urban surface waters, an event-based, one-year monitoring program was set up in separate storm sewers in Berlin. Monitoring points were selected in 5 catchments of different urban structures (old building areas <1930, newer building areas >1950, single houses with gardens, roads >7500 vehicles/day and commercial areas) to consider catchment-specific differences. Storm events of different characteristics were sampled up to four hours during different seasons by automatic samplers triggered by flow meters. Volume-proportional samples (one composite sample per event) were analysed for a set of 100 parameters including 85 organic micropollutants (e.g. flame retardants, phthalates, pesticides/biocides, PAH), heavy metals and standard parameters. So far (70/88 samples), 60 organic micropollutants were at least once detected in stormwater runoff of the investigated catchment types. Concentrations were highest for phthalates with average concentrations of 13 µg/L for diisodecyl phthalate. For heavy metals, concentrations were highest for zinc (average: 950 µg/L). Results also showed catchment-specific differences for many compounds as well as seasonal differences for selected pollutants which can be used to improve micropollutant strategies and potentially prevent loads at the source.

We investigate water quality of a small urban river during dry and wet weather conditions, including both standard parameters and trace organics. The monitored river stretch receives both effluents from WWTP as well as (separate) stormwater runoff of an impervious area of 11 km2. Results show increases in concentrations in the river during rain events with a factor > 20 for zinc, polycyclic aromatic hydrocarbons, two herbicides and one flame retardant. Also, substances which are expected both in WWTP effluent and in stormwater effluents were detected at important concentrations in the river during wet weather, such as the corrosion inhibitor Benzotriazole (0.8 µg/L on average) and the plasticizer Diisodecyl phthalate (4.0 µg/L on average). The presented results are preliminary and will be complemented by more results and substances as well as an assessment of the relevance of the findings.

Stormwater treatment technologies to manage runoff during rain events are primarily designed to reduce flood risks, settle suspended solids and concurrently immobilise metals and nutrients. Life Cycle Assessment (LCA) is scarcely documented for stormwater systems despite their ubiquitous imple- mentation. LCA modelling quantified the environmental impacts associated with the materials, con- struction, transport, operation and maintenance of different stormwater treatment systems. A pre- fabricated concrete vortex unit, a sub-surface sandfilter and a raingarden, all sized to treat a func- tional unit of 35 m3 of stormwater runoff per event, were evaluated. Eighteen environmental mid-point metrics and three end-point ‘damage assessment’ metrics were quantified for each system's lifecycle. Climate change (kg CO2 eq.) dominated net environmental impacts, with smaller contributions from human toxicity (kg 1,4-DB eq.), particulate matter formation (kg PM10 eq.) and fossil depletion (kg oil eq.). The concrete unit had the highest environmental impact of which 45% was attributed to its maintenance while impacts from the sandfilters and raingardens were dominated by their bulky ma- terials (57%) and transport (57%), respectively. On-site infiltrative raingardens, a component of green infrastructure (GI), had the lowest environmental impacts because they incurred lower maintenance and did not have any concrete which is high in embodied CO2. Smaller sized raingardens affording the same level of stormwater treatment had the lowest overall impacts reinforcing the principle that using fewer resources reduces environmental impacts. LCA modelling can serve as a guiding tool for practitioners making environmentally sustainable solutions for stormwater treatment.

Rain water runoff is the largest untreated source of potentially high loads of micro pollutants to urban surface waters. Given first findings it can be expected that new rainwater based micro pollutants will be included in future lists of priority substances of the EU Water Framework Directive (WFD). Knowledge of the type and amount of micro pollutants is (therefore) pivotal for enabling good management. Pollutant concentrations depend heavily on rain event characteristics such as rain depth, mean rain rate, intensity, duration and dry-weather-period. As rainfall is usually reported to fall in events and is separated by rainless intervals of a certain duration, the minimum interevent time (MIT) plays a major role within the criteria for defining such rain events. Surprisingly little attention has been paid to the importance of rain event definitions in similar published works, which limits the significance of the results and their comparability to other researches. That is why this work aims to identify independent rain events from a pluviograph record with the help of further hydraulic data. It is also the goal to examine rainfall characteristics of (5) sub-catchments within in the larger catchment Berlin and their sensibility through the variation of rain event definitions, like the very important Minimum-Inter-event Time Definition (MITD). Several rain gauges close-by as well as sensors to measure the water level and the flow inside a storm water sewer of a separated sewage system supply the necessary data. Additionally a number of criteria, found in literature, help to identify the most stable definition of a rain event for these catchments. It is also the intention to set the basis for further analysis (within the project this thesis is realized in) in order to generate the most adequate concentration data of micro pollutants in Berlin’s urban rain water runoff, as this definition will play a major role for further project analysis. Moreover this work intents to emphasize the relevance of the selection and documentation of rain event criteria in studies that apply event-based data analysis.

Urban stormwater runoff is a potential entrance pathway for a wide range of anthropogenic trace pollutants, like biocides, plasticizers, heavy metals or flame retardants, to urban lakes and rivers. However, little is known on dependencies of the occurrence of these trace pollutants on rain event characteristics and climate or seasonal influences. Furthermore, the importance of such dependencies for the calculation of loads and the uncertainties involved are unclear. This thesis evaluates possible correlations between trace pollutant concentrations in urban stormwater runoff and rain event characteristics together with further climate and seasonal influences, based on a large set of measurements from the project “Trace organics in Berlin stormwater runoff (OgRe)”. Here, samples were taken in a one-year monitoring program for five stormwater catchments representing specific urban structure types. Additionally, this thesis investigates whether the consideration of those correlations is necessary for the calculation of loads or whether the use of a mean concentration is sufficient. A method for the correlation analysis is developed and applied to the data, under the requirement to use just one influencing factor (predictor) per correlation and to keep the models simple. Regression models are fitted with regard to normal and log-normal error distributions. The models are evaluated regarding their goodness of fit using the Nash-Sutcliffe efficiency, the log-likelihood ratio, and the prediction coefficient of determination. For 45 out of 48 of the considered substances at least one correlation (i.e. in one of the five catchments) with rain or climate predictors is found. In addition, it is demonstrated that seasonal influences have an effect on substance concentrations for 25 out of 48 substances. Thus, the selected predictor values prove useful to explain the measured concentrations. Only 11 substances show the same correlation with a rain/climate predictor in four catchments and none in all five catchments. So, while concentrations for single events in one catchment can be well explained by the correlations, overall concentration patterns seem to be strongly influenced by the catchment, i.e. its urban structure type. Furthermore, it is shown that the assumption of a normally distributed error does not represent the data adequately in most cases. Consideration of a log-normal error distribution improves most regression models significantly. Regarding single substances, the correlation analysis helps to explain observed patterns. For instance, terbuthylazine, an agricultural pesticide, was only detected during typical application months of May and June, with the same observation in all five catchments. Accordingly, atmospheric deposition from the agricultural surroundings seems a reasonable explanation. In a second example, nicotine was found at very high concentrations in four catchments for low rain event durations, showing a strong decrease with increasing duration. This behavior can be explained by the fast elution of nicotine from cigarette butts within the first minutes of a rain event, followed by dilution during longer rain events. An exemplary load estimation based on a 30-year rain series for Berlin using a Monte Carlo simulation demonstrates that the use of regression models versus mean concentrations can lead to very different results. The reason lies in the selection of sampled rain events which are not distributed according their contribution to the total runoff volume (there should be more small to medium rain events, which contribute more to the total runoff volume). In conclusion, errors in the load estimation can result from i) using a mean concentration instead of a valid correlation, but also from ii) using a non-valid correlation. This underlines the importance of performing a correlation analysis before load calculations, but also the importance of a critical evaluation of the sample data and the correlations. For the latter, a combined evaluation along several goodness-of-fit metrics is suggested, together with plausibility checks of the correlation and of the considered range of values within which the regression model is applied.

In recent years several ways of recovering phosphorous from municipal wastewater have been developed. Depending on the applied technology the recovered products vary significantly concerning the concentrations of heavy metals and organic residues. Within the boundaries of data quality and present uncertainties a comparative risk assessment of seven secondary phosphorus fertilizers, sewage sludge, raw ash and triple super phosphate has been conducted for PCDD/Fs, PCBs, PAHs, As, Cd, Cr, Cu, Hg, Ni, Pb and Zn. Local exposure assessment was done using the kinetic model of the European Union’s Technical Guidance Document for all substances accounting for both fertilization and average atmospheric deposition. For substances of concern (Cd and Zn) the exposure was additionally refined using a solute transport model (HYDRUS-1D) and a precipitation model (Visual MINTEQ-software). An annual fertilizer amount equivalent to 60 kg P2O5/ ha × year by these products is assumed. In order to account for potential accumulation a time span of 100 years is modelled. Results indicate that out of the selected 11 (groups of) chemicals only cadmium and zinc are of concern. Regarding soil organisms, zinc is of concern for sludge, raw ash and one of the seven secondary phosphate fertilizers in case of soil-pH above pH 6.0. Regarding groundwater, cadmium and zinc are of concern below pH 6.0 since mobilization at this pH level increase significantly. No risk is expected regarding the endpoint humans. Among the investigated products struvites have shown the lowest phosphorus-specific heavy metal contents. For ash related products more data from full scale operations are needed to reduce still existing uncertainties like the influence of raw wastewater quality and WWTP operation on the final product.